A systematic review of community pharmacist therapeutic knowledge of dietary supplements

Background: Internationally, the use of dietary supplements has been growing rapidly. Patient support for pharmacist sales of nutritional and dietary supplements is also strong. The increase in demand for nutritional and dietary supplements and subsequent advice about these products, however, makes it necessary that pharmacists maintain a contemporary knowledge of the area. Aim of review: This systematic review was conducted to examine the current evidence regarding the level of the nutritional and dietary supplement knowledge of community pharmacists and their understanding of their therapeutic effects. Method: Electronic databases including Medline, Scopus, Embase, CINAHL, Scifinder and the Cochrane Controlled Trials Register were searched. Studies assessing nutritional knowledge of pharmacists in community pharmacies were eligible for inclusion. All languages and study designs were considered. Study results were analysed and pharmacist knowledge scores were given out of 100 . Results: From 5594 studies identified, nine met the inclusion criteria. Each study tested pharmacist knowledge with predetermined questions calculating results as the number of questions answered correctly. These knowledge scores were converted to a percentage score for the purpose of this paper. The median knowledge score across all papers was 64%. A lack of studies assessing community pharmacist's knowledge of commonly sold vitamins and minerals was observed. Conclusions Global community pharmacist knowledge of dietary supplements appears to be poor. Community pharmacists have an professional responsibility to provide accurate health information about dietary supplements as they do for any other therapies they provide to patients. Further research including that which assesses pharmacist's therapeutic knowledge of commonly sold vitamins and minerals is suggested.

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Human papillomavirus infection and vaccination: Awareness and knowledge of HPV and acceptability of HPV vaccine among mothers of teenage daughters in Weihai, Shandong, China

In preparation for the introduction of human papillomavirus (HPV) vaccine, we investigated awareness and knowledge of HPV/HPV vaccine and potential acceptability to HPV vaccine among mothers with a teenage daughter in Weihai, Shandong, China. A cross-sectional survey was conducted in 2013 with a sample of 1850 mothers who had a daughter (aged 9–17 years) attending primary, junior and senior high schools. In the final sample (N = 1578, response rate 85.30%), awareness of HPV was reported by 305 (19.32%) mothers. Awareness varied significantly by daughter’s age (P<0.01), mother’s education level (P<0.01), mother’s occupation (P<0.01), household income (P<0.01) and residence type (P<0.01). Knowledge about HPV/HPV vaccine was poor with a mean total score of 3.56 (SD = 2.40) out of a possible score of 13. Mothers with a higher education level reported higher levels of knowledge (P = 0.02). Slightly more than one-fourth (26.49%) of mothers expressed their potential acceptability of HPV vaccine for their daughters. Acceptability increased along with increased daughters’ age (P<0.01), household income (P<0.01) and knowledge level (P<0.01). House wives and unemployed mothers had the highest acceptability (P<0.01). The most common reasons for not accepting HPV vaccination were “My daughter is too young to have risk of cervical cancer (30.95%)”, “The vaccine has not been widely used, and the decision will be made after it is widely used (24.91%)”, “Worry about the safety of the vaccine (22.85%)”. Awareness and knowledge of HPV/HPV vaccines are poor and HPV vaccine acceptability is low among these Chinese mothers. These results may help inform appropriate health education programs in this population.

Knowledge discovery from tree databases using balanced optimal search

This research is a step forward in discovering knowledge from databases of complex structure like tree or graph. Several data mining algorithms are developed based on a novel representation called Balanced Optimal Search for extracting implicit, unknown and potentially useful information like patterns, similarities and various relationships from tree data, which are also proved to be advantageous in analysing big data. This thesis focuses on analysing unordered tree data, which is robust to data inconsistency, irregularity and swift information changes, hence, in the era of big data it becomes a popular and widely used data model.

Digital access to knowledge in the preschool classroom: Reports from Australia

Australian preschool teachers’ use of Web-searching in their classroom practice was examined (N = 131). Availability of Internet-enabled digital technology and the contribution of teacher demographic characteristics, comfort with digital technologies and beliefs about their use were assessed. Internet-enabled technologies were available in 53% (n = 69) of classrooms. Within these classrooms, teacher age and beliefs predicted Web-searching practice. Although comfortable with digital access of knowledge in their everyday life, teachers reported less comfort with Web-searching in the context of their classroom practice. The findings identify the provision of Internet-enabled technologies and professional development as actions to support effective and confident inclusion of Web-searching in classrooms. Such actions are necessary to align with national policy documents that define acquisition of digital literacies as a goal and assert digital access to knowledge as an issue of equity.

e-Extinction: an illusion of knowledge, the presence of ignorance, or evolutionary fate?

At present, the rate of small firm adoption of the Internet's ubiquitous World Wide Web (the web) far exceeds the actual exploitation its commercial potential. An inability to strategically acquire, comprehend and use external knowledge is proposed as a major barrier to optimal exploitation of the Internet. This paper discusses the limitations of applying market orientation theory to explain and guide small firm exploitation of the web. Absorptive capacity is introduced as an alternative theory that when viewed from an evolutionary perspective provides potentially more insightful discussion. An inability to detect emerging business model dominant designs is suggested to be a mixture of the nature of the technology that supports the Internet and underdeveloped small firm knowledge processing capabilities. We conclude with consideration of the practical and theoretical implications that arise from the paper.

The perfect corporate fit: New knowledge for new times

This study examines the impact of corporate practice on schooling and on teachers' professional development at the end of the millennium. It is argued that the production of new forms of knowledge is creating new sites of struggle over who owns educational knowledge, and this has profound implications for professional identity formation in all areas of social and economic endeavour, including education. As schools are re-shaped into corporations, school administrators and teachers are under increasing pressure to improve their productivity and to develop themselves as enterprising leaders and managers. To do so they are drawing more and more heavily on the growing non-academic literature of selfimprovement and self-development. Concern is expressed that such literature tends to value mindless optimism over radical doubt.

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action: Food composition

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food composition for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action: Food labeling

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food labeling for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Food promotion

Reviews and synthesizes evidence to make recommendations on policy actions improve food environments in the area of food promotion for NSW Health

Creating healthy food environments in N.S.W.: A knowledge and evidence synthesis to inform advocacy and action: Food pricing

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food pricing for NSW Health

Creating healthy food environments in N.S.W.: A knowledge and evidence synthesis to inform advocacy and action: Food provision

Reviews and synthesizes evidence to produce evidence-based recommendations on policy actions to improve food provision for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Food retail

Reviews and synthesizes nutrition policy actions to improve food retail for NSW Health

Creating healthy food environments in NSW: A knowledge and evidence synthesis to inform advocacy and action. Seven separate documents across the domains: Overview

Summaries evidence across seven domains of potential food policy action to improve food environments and food supply to prevent obesity for NSW Health

Standardization efforts: The relationship between knowledge dimensions, search processes and innovation outcomes

We explore how a standardization effort (i.e., when a firm pursues standards to further innovation) involves different search processes for knowledge and innovation outcomes. Using an inductive case study of Vanke, a leading Chinese property developer, we show how varying degrees of knowledge complexity and codification combine to produce a typology of four types of search process: active, integrative, decentralized and passive, resulting in four types of innovation outcome: modular, radical, incremental and architectural. We argue that when the standardization effort in a firm involves highly codified knowledge, incremental and architectural innovation outcomes are fostered, while modular and radical innovations are hindered. We discuss how standardization efforts can result in a second-order innovation capability, and conclude by calling for comparative research in other settings to understand how standardization efforts can be suited to different types of search process in different industry contexts.